Statistical Paradigms : Recent Advances And Reconciliations
by Ashis Sengupta /
2014 / English / PDF
2.9 MB Download
This volume consists of a collection of research articles on classical and emerging Statistical Paradigms — parametric, non-parametric and semi-parametric, frequentist and Bayesian — encompassing both theoretical advances and emerging applications in a variety of scientific disciplines. For advances in theory, the topics include: Bayesian Inference, Directional Data Analysis, Distribution Theory, Econometrics and Multiple Testing Procedures. The areas in emerging applications include: Bioinformatics, Factorial Experiments and Linear Models, Hotspot Geoinformatics and Reliability. Readership: Researchers, professionals and advanced students working on Bayesian and frequentist approaches to statistical modeling and on interfaces for both theory and applications.
